Effective human machine interaction systems are need of the time so the work carried out deals with one of such significant HMI tasks- automatic emotion recognition. The experimentation carried out for this study is focused to facial expressions based emotion recognition. Two techniques of emotion recognition based on hybrid features are designed and experimented using JAFFE database. The first technique referred as "Hybrid Method1" is designed around feature descriptor obtained through local

more »

... rectional number & principal component analysis and feed forward neural network used as classifier. The second technique referred as "Hybrid Method 2" is designed around feature descriptor obtained through histogram of oriented gradients, local binary pattern and Gabor filters. PCA- principal component analysis is used for dimensionality reduction of feature descriptor and k-nearest neighbors as classifier. The average emotion recognition accuracy achieved through method 1 and method 2 is 85.24% and 93.86% respectively. Effectiveness of both the techniques is compared on the basis of performance parameters such as accuracy, false positive rate, false negative rate and emotion recognition time. Emotion recognition has wide application areas so the work carried out can be applied for suitable application development.